Traditionally, many modern processes involve an analysis of a large number of time-consuming events. For example, a malware protection model may require file scans of thousands of objects, where each scan requires five to ten milliseconds of processing time for a local scan and two hundred to four hundred milliseconds of processing time for a cloud lookup scan. However, traditional methodologies for minimizing an amount of these time-consuming analyses have generally exhibited various limitations.
For example, traditional analysis minimization methodologies such as caching scanned objects and events may not function for events such as write scans. Additionally, such traditional analysis minimization methodologies may not work well on objects that frequently change, as new analysis may be always required for such objects. Further, such traditional analysis minimization methodologies may have an associated cost (e.g., cache lookup) that may result in reduced overall analysis performance. There is thus a need for addressing these and/or other issues associated with the prior art.